Robots and artificial intelligence have proven to be almost 15% more accurate in detecting faults in wind turbines. The Innovate UK Research and Development project, which has been ongoing in collaboration between Perceptual Robotics and the University of Bristol for an initial two years before being extended for a further one with DNV, involved the partners incorporating fully-automated surface defect detection into the data-processing pipeline for wind turbine inspections.It is the first time the processing of the images was carried out fully automated. The project showed the partners’ unique system had a 14% improvement in fault detection accuracy when compared with expert humans carrying out the same inspections. The initial first two years of the project focused on offshore wind turbine inspections before being extended for a further year to consider validation of results in both onshore and extreme, offshore environments. The partners focused on demonstrating the capabilities of the inspection system by carrying out end-to-end validating and verifying of the data system; determining how the data collection process can be auditable and traceable, and analysing the way the performance is measured to ensure it is as accurate as possible.
